The Science of Building Great Teams - Part 2

This a duplicated article from the Harvard Business Journal from April 2012. It is written by Alex “Sandy” Pentland and it is still relevant today.

Overcoming the Limits of Observation

When we sense esprit de corps, that perception doesn’t come out of the blue; it’s the result of our innate ability to process the hundreds of complex communication cues that we constantly send and receive.

But until recently we had never been able to objectively record such cues as data that we could then mine to understand why teams click. Mere observation simply couldn’t capture every nuance of human behavior across an entire team. What we had, then, was only a strong sense of the things—good leadership and followership, palpable shared commitment, a terrific brainstorming session—that made a team greater than the sum of its parts.

Recent advances in wireless and sensor technology, though, have helped us overcome those limitations, allowing us to measure that ineffable “It factor.” The badges developed at my lab at MIT are in their seventh version. They generate more than 100 data points a minute and work unobtrusively enough that we’re confident we’re capturing natural behavior. (We’ve documented a period of adjustment to the badges: Early on, people appear to be aware of them and act unnaturally, but the effect dissipates, usually within an hour.) We’ve deployed them in 21 organizations over the past seven years, measuring the communication patterns of about 2,500 people, sometimes for six weeks at a time.

With the data we’ve collected, we’ve mapped the communication behaviors of large numbers of people as they go about their lives, at an unprecedented level of detail. The badges produce “sociometrics,” or measures of how people interact—such as what tone of voice they use; whether they face one another; how much they gesture; how much they talk, listen, and interrupt; and even their levels of extroversion and empathy. By comparing data gathered from all the individuals on a team with performance data, we can identify the communication patterns that make for successful teamwork.

Those patterns vary little, regardless of the type of team and its goal—be it a call center team striving for efficiency, an innovation team at a pharmaceutical company looking for new product ideas, or a senior management team hoping to improve its leadership. Productive teams have certain data signatures, and they’re so consistent that we can predict a team’s success simply by looking at the data—without ever meeting its members.

We’ve been able to foretell, for example, which teams will win a business plan contest, solely on the basis of data collected from team members wearing badges at a cocktail reception. (See “Defend Your Research: We Can Measure the Power of Charisma,” HBR January–February 2010.) We’ve predicted the financial results that teams making investments would achieve, just on the basis of data collected during their negotiations. We can see in the data when team members will report that they’ve had a “productive” or “creative” day.

The data also reveal, at a higher level, that successful teams share several defining characteristics:

1. Everyone on the team talks and listens in roughly equal measure, keeping contributions short and sweet.

2. Members face one another, and their conversations and gestures are energetic.

3. Members connect directly with one another—not just with the team leader.

4. Members carry on back-channel or side conversations within the team.

5. Members periodically break, go exploring outside the team, and bring information back.

The data also establish another surprising fact: Individual reasoning and talent contribute far less to team success than one might expect. The best way to build a great team is not to select individuals for their smarts or accomplishments but to learn how they communicate and to shape and guide the team so that it follows successful communication patterns.

The Key Elements of Communication

In our research we identified three aspects of communication that affect team performance. The first is energy,which we measure by the number and the nature of exchanges among team members. A single exchange is defined as a comment and some acknowledgment—for example, a “yes” or a nod of the head. Normal conversations are often made up of many of these exchanges, and in a team setting more than one exchange may be going on at a time.

The most valuable form of communication is face-to-face. The next most valuable is by phone or videoconference, but with a caveat: Those technologies become less effective as more people participate in the call or conference. The least valuable forms of communication are e-mail and texting. (We collect data on those kinds of communication without using the badges.

Still, the number of face-to-face exchanges alone provides a good rough measure of energy.) The number of exchanges engaged in, weighted for their value by type of communication, gives each team member an energy score, which is averaged with other members’ results to create a team score.

Energy levels within a team are not static. For instance, in my research group at MIT, we sometimes have meetings at which I update people on upcoming events, rule changes, and other administrative details. These meetings are invariably low energy. But when someone announces a new discovery in the same group, excitement and energy skyrocket as all the members start talking to one another at once.

The second important dimension of communication isengagement, which reflects the distribution of energy among team members. In a simple three-person team, engagement is a function of the average amount of energy between A and B, A and C, and B and C. If all members of a team have relatively equal and reasonably high energy with all other members, engagement is extremely strong. Teams that have clusters of members who engage in high-energy communication while other members do not participate don’t perform as well. When we observed teams making investment decisions, for instance, the partially engaged teams made worse (less profitable) decisions than the fully engaged teams. This effect was particularly common in far-flung teams that talked mostly by telephone.

The third critical dimension, exploration, involves communication that members engage in outside their team. Exploration essentially is the energy between a team and the other teams it interacts with. Higher-performing teams seek more outside connections, we’ve found. We’ve also seen that scoring well on exploration is most important for creative teams, such as those responsible for innovation, which need fresh perspectives.

To measure exploration, we have to deploy badges more widely in an organization. We’ve done so in many settings, including the MIT Media Lab and a multinational company’s marketing department, which comprised several teams dedicated to different functions.

Our data also show that exploration and engagement, while both good, don’t easily coexist, because they require that the energy of team members be put to two different uses. Energy is a finite resource. The more that people devote to their own team (engagement), the less they have to use outside their team (exploration), and vice versa.

But they must do both. Successful teams, especially successful creative teams, oscillate between exploration for discovery and engagement for integration of the ideas gathered from outside sources. At the MIT Media Lab, this pattern accounted for almost half of the differences in creative output of research groups. And in one industrial research lab we studied, it distinguished teams with high creativity from those with low creativity with almost 90% accuracy.

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